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ECSE 6961 The Wireless Channel. Shiv Kalyanaraman shivkuma@ecse.rpi.edu Google: “Shiv RPI”. Slides based upon books by Tse/Viswanath, Goldsmith, Rappaport, J.Andrews etal. Wireless Channel is Very Different!. Wireless channel “feels” very different from a wired channel.
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ECSE 6961The Wireless Channel Shiv Kalyanaraman shivkuma@ecse.rpi.edu Google: “Shiv RPI” Slides based upon books by Tse/Viswanath, Goldsmith, Rappaport, J.Andrews etal
Wireless Channel is Very Different! • Wireless channel “feels” very different from a wired channel. • Not a point-to-point link • Variable capacity, errors, delays • Capacity is shared with interferers • Characteristics of the channel appear to change randomly with time, which makes it difficult to design reliable systems with guaranteed performance. • Cellular model vs reality: Cellular system designs are interference-limited, i.e. the interference dominates the noise floor
Basic Ideas: Path Loss, Shadowing, Fading • Variable decay of signal due to environment, multipaths, mobility Source: A. Goldsmith book
Attenuation, Dispersion Effects: ISI! Inter-symbol interference (ISI) Source: Prof. Raj Jain, WUSTL
Wireless Multipath Channel Channel varies at two spatial scales: * Large scale fading: path loss, shadowing * Small scale fading: Multi-path fading (frequency selectivity, coherence b/w, ~500kHz), Doppler (time-selectivity, coherence time, ~2.5ms)
Game plan • We wish to understand how physical parameters such as • carrier frequency • mobile speed • bandwidth • delay spread • angular spread impact how a wireless channel behaves from the cell planning and communication system point of view. • We start with deterministic physical model and progress towards statistical models, which are more useful for design and performance evaluation.
Large-scale fading: Cell-Site Planning • In free space, received power attenuates like 1/r2. • With reflections and obstructions, can attenuate even more rapidly with distance. Detailed modelling complicated. • Time constants associated with variations are very long as the mobile moves, many seconds or minutes. • More important for cell site planning, less for communication system design.
Path Loss Modeling • Maxwell’s equations • Complex and impractical • Free space path loss model • Too simple • Ray tracing models • Requires site-specific information • Empirical Models • Don’t always generalize to other environments • Simplified power falloff models • Main characteristics: good for high-level analysis
Free-Space-Propagation • If oscillating field at transmitter, it produces three components: • The electrostatic and inductive fields that decay as 1/d2 or 1/d3 • The EM radiation field that decays as 1/d (power decays as 1/d2)
Electric (Far) Field & Transfer Function • Tx: a sinusoid: cos 2ft • Electric Field: source antenna gain (s) • Product of antenna gains () • Consider the function (transfer function) • The electric field is now: Linearity is a good assumption, but time-invariance lost when Tx, Rx or environment in motion
Free-space and received fields: Path Loss (power flux density Pd) Note: Electric Field (E) decays as 1/r, but Power (Pd) decays as 1/r2 Path Loss in dB:
Decibels: dB, dBm, dBi • dB (Decibel) = 10 log 10 (Pr/Pt)Log-ratio of two signal levels. Named after Alexander Graham Bell. For example, a cable has 6 dB loss or an amplifier has 15 dB of gain. System gains and losses can be added/subtracted, especially when changes are in several orders of magnitude. • dBm (dB milliWatt)Relative to 1mW, i.e. 0 dBm is 1 mW (milliWatt). Small signals are -ve (e.g. -83dBm). Typical 802.11b WLAN cards have +15 dBm (32mW) of output power. They also spec a -83 dBm RX sensitivity (minimum RX signal level required for 11Mbps reception). For example, 125 mW is 21 dBm and 250 mW is 24 dBm. (commonly used numbers) • dBi (dB isotropic) for EIRP (Effective Isotropic Radiated Power) The gain a given antenna has over a theoretical isotropic (point source) antenna. The gain of microwave antennas (above 1 GHz) is generally given in dBi. • dBd (dB dipole)The gain an antenna has over a dipole antenna at the same frequency. A dipole antenna is the smallest, least gain practical antenna that can be made. A dipole antenna has 2.14 dB gain over a 0 dBi isotropic antenna. Thus, a simple dipole antenna has a gain of 2.14 dBi or 0 dBd and is used as a standard for calibration. The term dBd (or sometimes just called dB) generally is used to describe antenna gain for antennas that operate under 1GHz (1000Mhz).
dB calculations: Effective Isotropic Radiated Power (EIRP) • EIRP (Effect Isotropic Radiated Power): effective power found in the main lobe of transmitter antenna. • EIRP = PtGt • In dB, EIRP is equal to sum of the antenna gain, Gt (in dBi) plus the power, Pt (in dBm) into that antenna. • For example, a 12 dBi gain antenna fed directly with 15 dBm of power has an Effective Isotropic Radiated Power (EIRP) of: 12 dBi + 15dBm = 27 dBm (500 mW).
Path Loss (Example 1): Carrier Frequency • Note: effect of frequency f: 900 Mhz vs 5 Ghz. • Either the receiver must have greater sensitivity or the sender must pour 44W of power, even for 10m cell radius! 10m W Source: A. Goldsmith book
Path Loss (Example 2), Interference & Cell Sizing • Desired signal power: • Interference power: • SIR: • SIR is much better with higher path loss exponent ( = 5)! • Higher path loss, smaller cells => lower interference, higher SIR Source: J. Andrews et al book
Path Loss: Range vs Bandwidth Tradeoff • Frequencies < 1 GHz are often referred to as “beachfront” spectrum. Why? • 1. High frequency RF electronics have traditionally been harder to design and manufacture, and hence more expensive. [less so nowadays] • 2. Pathloss increases ~ O(fc2) • A signal at 3.5 GHz (one of WiMAX’s candidate frequencies) will be received with about 20 times less power than at 800 MHz (a popular cellular frequency). • Effective path loss exponent also increases at higher frequencies, due to increased absorption and attenuation of high frequency signals • Tradeoff: • Bandwidth at higher carrier frequencies is more plentiful and less expensive. • Does not support large transmission ranges. • (also increases problems for mobility/Doppler effects etc) • WIMAX Choice: • Pick any two out of three: high data rate, high range, low cost.
Ray Tracing • Models all signal components • Reflections • Scattering • Diffraction • Diffraction: signal “bends around” an object in its path to the receiver: • Diffraction Path loss exceeding 100 dB • Error of the ray tracing approximation is smallest when the receiver is many wavelengths from the nearest scatterer, and all the scatterers are large relative to a wavelength and fairly smooth. • Good match w/ empirical data in rural areas, along city streets (Tx/Rx close to ground), LAN with adjusted diffraction coefficients
s s l Reflection, Diffraction, Scattering • 900Mhz: ~ 30 cm • 2.4Ghz: ~ 13.9 cm • 5.8Ghz: ~ 5.75 cm Reflection/Refraction: large objects (>>) Scattering: small objects, rough surfaces (<): foilage, lamposts, street signs Diffraction/Shadowing: “bending” around sharp edges,
Classical 2-ray Ground Bounce model Source: A. Goldsmith book (derivation in book)
2-ray model observations • The electric field flips in sign canceling the LOS field, and hence the path loss is O(d-4) rather than O(d-2). • The frequency effectdisappears! • Similar phenomenon with antenna arrays. • Near-field, far-field detail explored in next slide: • Used for cell-design
2-ray model: distance effect, critical distance • d < ht: constructive i/f • ht < d < dc: constructive and destructive i/f (multipath fading upto critical distance) • dc < d: only destructive interference • Piecewise linear approximation w/ slopes 0, -20 dB/decade, -40 dB/decade Source: A. Goldsmith book
2-ray model example, cell design • Design the cell size to be < critical distance to get O(d-2) power decay in cell and O(d-4) outside! • Cell radii are typically much smaller than critical distance Source: A. Goldsmith book
10-Ray Model: Urban Microcells • Ground and 1-3 wall reflections • Falloff with distance squared (d−2)! • Dominance of the multipath rays which decay as d−2, … • … over the combination of the LOS and ground-reflected rays (the two-ray model), which decays as d−4. • Empirical studies: d−γ, where γ lies anywhere between two and six
Simplified Path Loss Model • Used when path loss dominated by reflections. • Most important parameter is the path loss exponent g, determined empirically. • Cell design impact: If the radius of a cell is reduced by half when the propagation path loss exponent is 4, the transmit power level of a base station is reduced by 12dB (=10 log 16 dB). • Costs: More base stations, frequent handoffs
Typical large-scale path loss Source: Rappaport and A. Goldsmith books
Empirical Models • Okumura model • Empirically based (site/freq specific) • Awkward (uses graphs) • Hata model • Analytical approximation to Okumura model • Cost 136 Model: • Extends Hata model to higher frequency (2 GHz) • Walfish/Bertoni: • Cost 136 extension to include diffraction from rooftops Commonly used in cellular system simulations
Empirical Path Loss: Okamura, Hata, COST231 • Empirical models include effects of path loss, shadowing and multipath. • Multipath effects are averaged over several wavelengths: local mean attenuation (LMA) • Empirical path loss for a given environment is the average of LMA at a distance d over all measurements • Okamura: based upon Tokyo measurements. 1-100 lm, 150-1500MHz, base station heights (30-100m), median attenuation over free-space-loss, 10-14dB standard deviation. • Hata: closed form version of Okamura • COST 231: Extensions to 2 GHz Source: A. Goldsmith book
Indoor Models • 900 MHz: 10-20dB attenuation for 1-floor, 6-10dB/floor for next few floors (and frequency dependent) • Partition loss each time depending upton material (see table) • Outdoor-to-indoor: building penetration loss (8-20 dB), decreases by 1.4dB/floor for higher floors. (reduced clutter) • Windows: 6dB less loss than walls (if not lead lined)
Path Loss Models: Summary • Path loss models simplify Maxwell’s equations • Models vary in complexity and accuracy • Power falloff with distance is proportional to d2 in free space, d4 in two path model • General ray tracing computationally complex • Empirical models used in 2G/3G/Wimax simulations • Main characteristics of path loss captured in simple model Pr=PtK[d0/d]g
Shadowing • Log-normal model for shadowing r.v. ()
Log-Normal Shadowing • Assumption: shadowing is dominated by the attenuation from blocking objects. • Attenuation of for depth d: s(d) = e−αd, (α: attenuation constant). • Many objects: s(dt) = e−α∑ di= e−αdt , dt= ∑ diis the sum of the random object depths • Cental Limit Theorem (CLT): αdt = log s(dt) ~ N(μ, σ). • log s(dt) is therefore log-normal
dBm Outage Probability w/ Shadowing • Need to improve receiver sensitivity (i.e. reduce Pmin) for better coverage.
Shadowing: Modulation Design • Simple path loss/shadowing model: • Find Pr: • Find Noise power:
Shadowing: Modulation Design (Contd) • SINR: • Without shadowing ( = 0), BPSK works 100%, 16QAM fails all the time. • With shadowing (s= 6dB): BPSK: 16 QAM • 75% of users can use BPSK modulation and hence get a PHY data rate of 10 MHz · 1 bit/symbol ·1/2 = 5 Mbps • Less than 1% of users can reliably use 16QAM (4 bits/symbol) for a more desirable data rate of 20 Mbps. • Interestingly for BPSK, w/o shadowing, we had 100%; and 16QAM: 0%!
Small-Scale Fading: Rayleigh/Ricean Models,Multipath & Doppler
Small-scale Multipath fading: System Design • Wireless communication typically happens at very high carrier frequency. (eg. fc = 900 MHz or 1.9 GHz for cellular) • Multipath fading due to constructive and destructive interference of the transmitted waves. • Channel varies when mobile moves a distance of the order of the carrier wavelength. This is about 0.3 m for 900 Mhz cellular. • For vehicular speeds, this translates to channel variation of the order of 100 Hz. • Primary driver behind wireless communication system design.
Source #1: Single-Tap Channel: Rayleigh Dist’n • Path loss, shadowing => average signal power loss • Fading around this average. • Subtract out average => fading modeled as a zero-mean random process • Narrowband Fading channel: Each symbol is long in time • The channel h(t) is assumed to be uncorrelated across symbols => single “tap” in time domain. • Fading w/ many scatterers: Central Limit Theorem • In-phase (cosine) and quadrature (sine) components of the snapshot r(0), denoted as rI (0) and rQ(0) are independent Gaussian random variables. • Envelope Amplitude: • Received Power:
path-1 Power path-2 path-3 path-2 Path Delay path-1 path-3 Channel Impulse Response: Channel amplitude |h| correlated at delays . Each “tap” value @ kTs Rayleigh distributed (actually the sum of several sub-paths) Source #2: Multipaths: Power-Delay Profile multi-path propagation Mobile Station (MS) Base Station (BS)
Multipath: Time-Dispersion => Frequency Selectivity • The impulse response of the channel is correlated in the time-domain (sum of “echoes”) • Manifests as a power-delay profile, dispersion in channel autocorrelation function A() • Equivalent to “selectivity” or “deep fades” in the frequency domain • Delay spread: ~ 50ns (indoor) – 1s (outdoor/cellular). • Coherence Bandwidth: Bc = 500kHz (outdoor/cellular) – 20MHz (indoor) • Implications: High data rate: symbol smears onto the adjacent ones (ISI). Multipath effects ~ O(1s)
Set of multipaths changes ~ O(5 ms) Source #3: Doppler: Non-Stationary Impulse Response.
Doppler: Dispersion (Frequency) => Time-Selectivity • The doppler power spectrum shows dispersion/flatness ~ doppler spread (100-200 Hz for vehicular speeds) • Equivalent to “selectivity” or “deep fades” in the time domain correlation envelope. • Each envelope point in time-domain is drawn from Rayleigh distribution. But because of Doppler, it is not IID, but correlated for a time period ~ Tc (correlation time). • Doppler Spread: Ds ~ 100 Hz (vehicular speeds @ 1GHz) • Coherence Time: Tc = 2.5-5ms. • Implications: A deep fade on a tone can persist for 2.5-5 ms! Closed-loop estimation is valid only for 2.5-5 ms.
Fading Summary: Time-Varying Channel Impulse Response • #1: At each tap, channel gain |h| is a Rayleigh distributed r.v.. The random process is not IID. • #2: Response spreads out in the time-domain (), leading to inter-symbol interference and deep fades in the frequency domain: “frequency-selectivity” caused by multi-path fading • #3: Response completely vanish (deep fade) for certain values of t: “Time-selectivity” caused by doppler effects (frequency-domain dispersion/spreading)